Stanford Vision and Learning Lab

Gibson Environments: Real-World Perception for Embodied Agents

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The data skeleton from "3D Scene Graph: A Structure for Unified Semantics, 3D Space, and Camera" http://3dscenegraph.stanford.edu

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Class notes for CS 131.

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Released assignments for the Stanford's CS131 course on Computer Vision.

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A Simulation Environment to train Robots in Large Realistic Interactive Scenes

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RoboVat: A unified toolkit for simulated and real-world robotic task environments.

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Code for the CoRL 2019 paper AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers

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Code to evaluate a solution in the BEHAVIOR benchmark: starter code, baselines, submodules to iGibson and BDDL repos

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